Distributional Results for Model-Based Intrinsic Dimension Estimators

Understand

Modern datasets are characterized by a large number of features that may conceal complex dependency structures.

• To deal with this type of data, dimensionality reduction techniques are essential.
• Numerous dimensionality reduction methods rely on the concept of intrinsic dimension, a measure of the complexity of the dataset.
• In this article, we first review the TWO-NN model, a likelihood-based intrinsic dimension estimator recently introduced in the literature.